A busy comment section can look like proof that a story connected with readers. But new research complicates that picture: data-rich stories tend to draw fewer commenters, while the people who do participate contribute more analytical, evidence-rich responses. It turns out that publishers that focus on volume alone may be overlooking a different and potentially valuable kind of engagement.  

News stories often use statistics, data, and analysis to provide readers with more information and evidence. But adding more material can also make a story more demanding for readers to process and could attract less commentary. In fact, the way that information is presented is often associated with whether or not readers choose to comment – but also how they comment.  

New research from Avner Kantor and Sheizaf Rafaeli examines this relationship across 6,400 New York Times stories and nearly one million comments. Kantor and Rafaeli’s analysis shows that stories with more statistical information and a stronger analytical writing style are associated with fewer people participating in the comments. However, on stories with fewer participants, comments contain more external sources and use more analytical language. They also use less emotionally oriented language. 

More information can mean fewer commenters 

The study focuses specifically on participation in news comment sections. The researchers define participation as the number of unique people who leave top-level comments on each story. Replies between commenters are excluded. The researchers also examine the language and information the commenters use.  

Not every feature of a story has the same relationship with participation.  

How Story features relate to comment participation 

↓ Associated with fewer commenters 
Articles with more statistical information 
Articles with more analytical writing 

↔ No significant relationship with participation 
Articles with more external sources 
Articles with static data visualizations 

↑ Associated with more commenters 
Articles with more emotionally oriented writing 

The study reveals that comment volume does not tell the whole story. Smaller groups of commenters also communicate differently. The researchers call this a “participation filtering mechanism.” They argue that stories requiring greater cognitive effort can discourage some readers from commenting. On stories with lower participation, commenters tend to use more analytical language and external sources, and less emotionally oriented language. 

Data journalism is associated with analytical comments 

The study also finds differences between comments on The Upshot stories and traditional New York Times stories. The Upshot is the Times’ data journalism section. Even after accounting for individual story features and comment volume, comments on The Upshot stories are more analytical. They contain more statistics and external sources and rely less on emotionally oriented language.  

Who reads what and why 

The researchers identify two factors associated with these commenting patterns: who the journalism attracts and who ultimately chooses to comment. They argue that data journalism can attract readers who are more analytically oriented. The informational demands of an individual story can then further filter who participates in the comments. 

This distinction adds context for publishers because the audience discussing a story may already differ based on the type of journalism they choose to consume. The characteristics of an individual story are then associated with who decides to comment. The researchers describe audience self-selection and participation filtering as complementary processes that help explain these commenting patterns. 

Kantor and Rafaeli’s analysis offers publishers a broader view of comment activity. The research connects commenting patterns to both the type of journalism readers choose and how information is presented within individual stories. Comment volume remains one measure of participation, but it does not capture who participates or the characteristics of their comments.